Latest AI and machine learning research in infectious disease for healthcare professionals.
BACKGROUND: Accurately differentiating severe from nonsevere COVID-19 clinical types is critical for the health care system to optimize workflow. Current techniques lack the ability to accurately classify COVID-19 clinical types in patients, especially as SARS-CoV-2 continues to mutate. OBJECTIVE: We explore the predictability and interpretability of multiple state-of-the-art machine learning (ML)...
BACKGROUND: Predicting enterocutaneous fistula (ECF)-associated sepsis and mortality poses significant challenges in digital health care due to the disease's complexity and heterogeneous clinical manifestations. Current approaches that rely on single-modal data or traditional scoring systems often fail to capture the intricate immune-inflammatory dynamics and multisystem involvement in patients wi...
Despite the reduced impact of COVID-19 due to widespread vaccination and improved treatments, a critical need remains for accessible, scalable, and ra...
Antibody folding and aggregation are major challenges in the development of relevant reagents and therapeutics. Antibodies face a biophysical trade-of...
INTRODUCTION: Extranodal natural killer/T-cell lymphoma, nasal type (ENKTL), is a rare EBV-associated malignancy characterized by destructive tumors i...
Pneumonia remains a leading cause of in-hospital mortality worldwide. Current prognostic tools such as the IDSA/ATS severity score have meaningful lim...
Digitizing metadata on natural history specimen labels remains a critical bottleneck for biodiversity research. We present a transformative workflow i...
Nipah virus (NiV) and Hendra virus (HeV) are bat-borne zoonotic paramyxoviruses that cause severe and often fatal respiratory and neurological disease...
Coxiella burnetii is a highly virulent intracellular pathogen and the causative agent of acute and chronic Q fever in humans. Central to its pathogeni...
The primary objective of this study is to develop and validate robust data-driven models for accurately predicting bacterial growth inhibition induced...
This study uses the Levenberg-Marquardt strategy with feed forward neural networks (LMS-FNN) to inspect the Soret-Dufour effect on radiative hybrid na...
Field-effect transistor (FET)-based biosensors are promising tools for early infectious-disease detection; however, their real-world deployment is lim...
OBJECTIVE: To characterise temporal trends in antiretroviral therapy (ART) utilisation and forecast short-term changes in regimen distribution within ...
Necrotizing fasciitis (NF) and osteomyelitis (OM) are severe, limb-threatening infections with overlapping features, making early differentiation chal...
Respiratory syncytial virus (RSV) remains a major cause of severe acute respiratory infections across the life course, particularly in infants, older ...
Carcinoma of the gallbladder (CAGB) carries a poor prognosis. While alterations in the bile microbiome and lipidome have been linked to CAGB developme...
Mosquito-borne diseases remain a major global health challenge, disproportionately impacting low- and middle-income countries. Despite traditional con...
Squamous cell carcinomas of unknown primary (SCCUP), accounting for approximately 5% of head and neck malignancies, present significant clinical chall...
The global escalation of antibiotic resistance has renewed interest in antimicrobial peptides (AMPs) as promising alternatives to conventional antibio...
BACKGROUND: Artificial intelligence (AI) is increasingly applied in endourology to enhance surgical planning, risk stratification, and outcome predict...